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Controversial software claims to tell personality from your face

A start-up says its face-recognition tech can identify people's personality type from photos – and spot terrorists, paedophiles and poker players in crowds

Anyone for bingo?

Lioba Schneider/plainpicture

By Sally Adee

CAN software identify complex personality traits simply by analysing your face? Faception, a start-up in Tel Aviv, Israel, courted controversy this week when it claimed its tech does just that. And not just broad categories such as introvert or extrovert: Faception claims it can spot paedophiles, terrorists – and brand promoters.

Faception’s algorithm scours images of a person from a variety of sources, including uploaded photos, live-streamed video and mugshots in a database. It then encodes facial features, including width and height ratio, and key points – for example, the corners of the eyes and mouth.

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The controversial part is what happens next. Faception maps these features onto a set of 15 proprietary “classifiers” that it has developed over the past three years. Its categories include terrorist, paedophile, white-collar criminal, poker player, bingo player and academic. To come up with its custom archetypes, Itzik Wilf, Faception’s chief technology officer, says the system was trained on the facial features of thousands of images of known examples. The software only looks at facial features, he says, and ignores things like hairstyle and jewellery.

“Faception claims it can spot terrorists, paedophiles – and even brand promoters and bingo players“

Wilf says this has led to notable successes. When presented with the photos of the 11 people behind the 2016 Paris attacks, the algorithm was able to classify nine of them as terrorists. Similarly, it spotted 25 out of the 27 poker players in an image database.

The Faception site also lists more prosaic uses for its tech, including marketing, insurance underwriting and recruiting. “HR could use it to identify suitable candidates,” says Wilf.

Many machine vision researchers are crying foul, however, including Emin Gün Sirer at Cornell University in Ithaca, New York. “A classifier that tries to flag every single person of Arab descent could identify 9 out of the 11 Paris attackers at the cost of falsely flagging 370 million out of the 450 million Arabs in the world,” he says. “Such a classifier is completely useless.”

Wilf says that for each of their classifiers, the training sets of images run in the thousands. But for behaviours as uncommon as terrorism or paedophilia, this will still lead to a number of false positives and Wilf acknowledges this. “There are always accuracy issues with machine learning algorithms,” he says. For that reason, the algorithm will always defer to human judgement.

What that means in practice is unclear, as the human ability to infer personality from facial traits is only slightly better than chance, says David Perrett at the University of St Andrews in the UK.

Face recognition technology has been the subject of many ethics debates in recent years. Most recently, there was an outcry over FindFace, a Russian app which uses data from social network Vkontakte to enable users to identify people they snapped on the street.

“We would never license our IP to someone who would use it for those kinds of purposes,” says Wilf. But Gilad Bechar, a co-founder of the company, says one of its clients is an unnamed security contractor outside of the US.

“This is a new idea,” Wilf says. “New ideas are often greeted with friction.”

This article appeared in print under the headline “Spot that poker face”